NUS
 
ISS
 

Real Time Audio-Visual Sensing and Sense Making

Overview

Reference No TGS-2020001514
Part of Graduate Certificate in Intelligent Sensing Systems
Duration 4 days
Course Time 9.00am - 5.00pm
Enquiry Please email ask-iss@nus.edu.sg for more details

Curious about how machines can see and hear the world around us, transforming perceptions into actions?

This course is designed for professionals seeking to leverage audio and video analytics in their operations. This course offers a deep dive into the core technologies that enable machines to interpret audio-visual data, providing actionable intelligence in real-time to enhance business intelligence and operational efficiency.

Discover how these systems can empower robots to navigate autonomously and interact with their environment, or how they can be applied to human activity interpretation, real-time crowd surveillance, healthcare monitoring, and customer emotion recognition in retail. Through a blend of theoretical knowledge and hands-on workshop sessions, participants will gain practical skills to process, integrate, interpret, and respond to audio-visual data.

Course Content

  • Real-Time Video Sensing: Modelling and processing.
  • Real-Time Video Analytics: Motion analysis and object tracking (e.g., DeepSORT); video analytics using deep learning (e.g., C3D, Two-stream).
  • Real-Time Audio and Speech Analytics: Through the utilisation of deep learning (e.g., wav2vec, conformers).
  • Practicality: Practical case studies and workshops

This course is part of the Artificial Intelligence and Graduate Certificate in Intelligent Sensing Systems Series offered by NUS-ISS.

Key Takeaways

  • Recognise the requirements and potential of real-time audio-visual sensing technologies across diverse industrial applications.
  • Design and implement audio-visual sense-making methods tailored for industrial scenarios using machine learning.
  • Evaluate the effectiveness and impact of various real-time audio-visual sense-making technologies.
  • Critically analyse, evaluate, and synthesise information to address complex audio-visual sensing challenges.



    Who Should Attend

    • Software Developers and Engineers tasked with creating sophisticated audio-visual data sensing systems.
    • Data Scientists who specialise in the analysis of audio and visual data.
    • System Architects who integrate audio and visual data analytics into comprehensive solutions.
    • Product Managers/Owners and Consultants seeking expertise in audio and visual data sense-making to design, manage, and assess system applications.



    Prerequisites

  • Participants should have intermediate skills in Python programming (e.g. Numpy, Pandas), and/or OpenCV programming (e.g. able to apply filtering and transformation on the image).
  • Experiences in using Jupyter Notebooks, Google Colab and well-versed in package installation.
  • Participants must have an intermediate knowledge of computer vision at the level of Vision Systems (e.g. image processing, image classification and object detection using deep learning).



  • Course Logistics

    • No Printed Materials: Course materials are accessed digitally. Do kindly note that no printed copies of course materials will be issued.
    • Device Requirements: Bring an internet-enabled device (laptop, tablet, etc) with power chargers to access and download course materials.
    If you are bringing a laptop, kindly refer to the table below for the recommended tech specs:

     

     

    Minimum

    Recommended

    Operating Systems

    • Windows 7 above
    • Mac OS

    Laptop running the latest
    version of either Windows or
    Mac OS

    System Type

    32-bit

    64-bit

    Memory

    8 GB RAM

    16+ GB RAM

    Hard Drive

    256 GB disk size

     

    Others

    • An internet connection – broadband wired or wireless
    • Installation permissions (non-company laptops)
    • Keyboard
    • Mouse/Trackpad
    • Display
    • Power adapter (laptop battery might run out)

    DirectX 10 graphics card for graphics hardware acceleration

     
     



    Fees & Subsidies

    Fees for 2024
      Full Fee Singaporeans & PRs
    (self-sponsored)
    Full course fee S$3600 S$3600
    ISS Subsidy  - (S$360)
    Nett course fee S$3600 S$3240
    9% GST on nett course fee S$324 S$291.60
    Total nett course fee payable, including GST S$3924 S$3531.60
    Note:
    1. All fees and subsidies are valid from January 2024, unless otherwise advised.
    2. All self-sponsored Singaporeans aged 25 and above can use their SkillsFuture Credit to pay for course fees. For more information about SkillsFuture Credit, click here.
    3. From 1st January 2024, the GST will be increased to 9%.



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    Certificate

    Certificate of Completion
    Participants have to meet a minimum attendance rate of 75% and are required to pass the assessment to be issued a Certificate of Completion.



    Join Us

    Register now to start your journey of mastering Audio-Visual Intelligence capabilities.




    Preparing for Your Course

    NUS-ISS Course Registration Terms and Conditions

    Find out more.

    NUS-ISS and Learner’s Commitment and Responsibilities

    Find out more.

    WIFI Access

    WIFI access will be made available to participants.

    Venue

    NUS-ISS
    25 Heng Mui Keng Terrace
    Singapore 119615

    Click HERE for directions to NUS-ISS

    In the event of a change of venue, participants are advised to refer to the acceptance email sent one week prior to the commencement date.

    Course Confirmation

    All classes are subject to confirmation and NUS-ISS will send an acceptance email to participants one week prior to the commencement date. Confirmed registrants are to attend and complete all lectures, class exercises, workshops and assessments (where applicable). Additionally, all responses to feedbacks and surveys conducted by NUS-ISS and its partners must be submitted. All training and assessments will be delivered as described in the course webpage.

    General Enquiry

    Please feel free to write to ask-iss@nus.edu.sg if you have any enquiry or feedback.




    Course Resources

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